This paper can help you as it is based on a real application whose task was to recognize characters printed on metal ingots.
If the images calibrated in the sense that the height of a digit is always the same number of pixels then you are lucky, if not, you probably need to calibrate them or include magnification as an extra variable to optimize it.
Then you have to create a set of ten images for each font with a uniform background, calculate a Euclidean distance-transform to the edges, and use these to do chamfer matching which is a simple, accurate, reliable, and fast registration method for the segmented images.
For more information regarding the chamfer matching, refer the following link:
If you are looking to learn more about Artificial Intelligence then visit this Artificial Intelligence Course which will cover topics like Simulated annealing algorithm Euclidean distance, Pearson correlation coefficient, Brute force search algorithms, Backtracking, Traveling salesman problem, NeuroEvolution of augmenting topologies, Fitness function, Resolution algorithm,k-nearest neighbors algorithm, Markov model, Genetic algorithm, deep first iterative deeping and many more.